Redis vs Apache Cassandra

Struggling to choose between Redis and Apache Cassandra? Both products offer unique advantages, making it a tough decision.

Redis is a Development solution with tags like caching, inmemory, keyvalue-store.

It boasts features such as In-memory data structure store, Supports various data structures (strings, hashes, lists, sets, sorted sets, bitmaps, hyperloglogs, geospatial indexes, streams), Used as a database, cache, and message broker, Provides high performance and low latency, Supports replication, clustering, and high availability, Supports a wide range of programming languages, Provides a rich set of commands and APIs, Supports data persistence (RDB and AOF) and pros including High performance and low latency, Flexible and versatile data structures, Supports a wide range of use cases, Easy to set up and configure, Scalable and highly available, Open-source and free to use.

On the other hand, Apache Cassandra is a Databases product tagged with distributed, scalable, high-availability, fault-tolerant, wide-column-store.

Its standout features include Distributed database system, Linear scalability, Fault tolerance, Tunable consistency, Column-oriented database, Multi-datacenter replication, and it shines with pros like High availability, Fast writes, Tunable consistency, Flexible schema design, Linear scalability.

Feature	Redis	Apache Cassandra
Overall Score	1	1
Primary Category	Development	Databases

Product Overview

Redis

Description: Redis is an open-source, in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes and streams.

Apache Cassandra

Description: Apache Cassandra is a free, open-source, distributed NoSQL database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.

Key Features Comparison

Redis Features

• In-memory data structure store
• Supports various data structures (strings, hashes, lists, sets, sorted sets, bitmaps, hyperloglogs, geospatial indexes, streams)
• Used as a database, cache, and message broker
• Provides high performance and low latency
• Supports replication, clustering, and high availability
• Supports a wide range of programming languages
• Provides a rich set of commands and APIs
• Supports data persistence (RDB and AOF)

Apache Cassandra Features

• Distributed database system
• Linear scalability
• Fault tolerance
• Tunable consistency
• Column-oriented database
• Multi-datacenter replication

Pros & Cons Analysis

Redis

Pros

• High performance and low latency
• Flexible and versatile data structures
• Supports a wide range of use cases
• Easy to set up and configure
• Scalable and highly available
• Open-source and free to use

Cons

• In-memory nature can lead to data loss in case of system failures
• Complexity in setting up and maintaining a highly available Redis cluster
• Limited support for transactions and complex queries compared to traditional databases
• Potential for high memory usage, especially for large datasets

Apache Cassandra

Pros

• High availability
• Fast writes
• Tunable consistency
• Flexible schema design
• Linear scalability

Cons

• Eventual consistency only
• Complex data modeling
• No joins or transactions
• Limited query capabilities
• Steep learning curve

Pricing Comparison

Redis

• Open Source

Apache Cassandra

• Open Source